Bibliographic record
Abstract
The CountsThe same number of counts, 83, were conducted this past winter as in the previous winter.As we shall see, the similarity pretty much ends there. The WeatherAverage minimum and maximum temperatures for the count period (with 2022-23 records in brackets) were -7 to -1 °C (-17 to -13 °C), wind speeds 7 to 14 km/h (8 to 17 km/h), and snow depths 1 to 5 cm (18 to 39 cm).Weather conditions were thus on average much warmer and slightly calmer compared to the previous winter.Snow depths were way down; indeed, 20 counts reported no snow at all.The warm weather and lack of snow had a significant impact on the numbers and variety of birds, and mammals, recorded. The BirdsThe 167,411 birds counted was higher than the century average of around 127,000, and much higher than the previous winter's 98,499.Half of the 2023-24 total, almost 83,000 birds, were Canada Geese.The total number of species at 106, and number of species per count at 19.3, was the second highest ever.Comparable numbers from the previous winter were 86 and 17.7.Gardiner Dam had the most species on count day with 50, one short of the all-time record from Fort Walsh with 51 in 2001.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.167 | 0.074 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".